Adapting Behavior and Persistence via Reinforcement and Self-Emotion Mediated Exploration in a Social Robot

Gustavo Assuncao, Alessandra Sorrentino, Jorge Dias, Miguel Castelo-Branco, Paulo Menezes, Filippo Cavallo

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    Adaptability and behavioral diversity are core components of social interactions between humans. Naturally, these are traits research should strive to achieve in social robotics so agents may be better accepted and engage with their user peers. In this paper, we propose a novel activity modulation to increase behavioral diversity, based on a surprise-exploration correlation model, in a social robot undergoing behavioral optimization to user state and preference. This framework was tested with 21 participants to assess preferences as well as the impact that action variability and persistence would have on user perception of the robot. Results indicate a positive effect of persistence and variability over robot likability as well as user engagement, contributing insight for future research in social robotics.

    Original languageBritish English
    Title of host publication2023 32nd IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2023
    PublisherIEEE Computer Society
    Pages185-190
    Number of pages6
    ISBN (Electronic)9798350336702
    DOIs
    StatePublished - 2023
    Event32nd IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2023 - Busan, Korea, Republic of
    Duration: 28 Aug 202331 Aug 2023

    Publication series

    NameIEEE International Workshop on Robot and Human Communication, RO-MAN
    ISSN (Print)1944-9445
    ISSN (Electronic)1944-9437

    Conference

    Conference32nd IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2023
    Country/TerritoryKorea, Republic of
    CityBusan
    Period28/08/2331/08/23

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